当前位置: 首页> 研究成果> 学术论文> 正文

2020年研究成果

  1. JINYUAN CHANG, ERIC D. KOLACZYK, QIWEI YAO,2020,Discussion of ‘Network cross-validation by edge sampling’, Biometrika, 107, 2, 277–280

  2. Rui She, Shiqing Ling 2020),Inference in heavy-tailed vector error correction modelsJournal of Econometrics214, 433450

  3. Fode Zhang, Yimin Shi, 2020, Geometry on the statistical manifold induced by the degradation model with soft failure dataJournal of Computational and Applied Mathematics,363.211-222

  4. Guochang Wang, Fode Zhang, Heng Lian, 2020, Directional regression for functional dataJournal of Statistical Planning and Inference, 204.1-7

  5. F.D. Zhang, H.K.T. Ng, Y. Shi, Mis-Specification Analysis of Wiener Degradation Models by Using f-Divergence with Outliers. Reliability Engineering & System Safety, 195 (2020) 106751

  6. F.D. Zhang, X. Wang, R. Li, H. Lian. (2020)Randomized sketches for sparse additive models. Neurocomputing 385,80-87

  7. F.D. Zhang, W. Zhang, R Li, H Lian. (2020)Faster convergence rate for functional linear regression in reproducing kernel Hilbert spaces. Statistics 54,167-181

  8. F.D. Zhang, H.K.T. Ng, Y.M. Shi. Geometry on degradation models and mis-specification analysis by using α-divergence. Physica A 527(2020) 121343

  9. Zhang, F., Li, R., & Lian, H. Approximate nonparametric quantile regression in reproducing kernel Hilbert spaces via random projection. Information Sciences, 547, 244-254.

  10. Zhao, W., Zhang, F., Li, R., & Lian, H. (2020). Principal single-index varying-coefficient models for dimension reduction in quantile regression. Journal of Statistical Computation and Simulation, 90(5), 800-818.

  11. Lian, H., Zhang, F., & Lu, W. (2020). Randomized sketches for kernel CCA. Neural Networks.127,29-37.

  12. Wang, R., Wu, M., Shi, Y., Ng, H. K. T., & Zhang, F. (2020)The geometric structure on a degradation model with application to optimal design under a cost constraint. Journal of Computational and Applied Mathematics, 382, 113081.

  13. Mingxuan Cai, Mingwei Dai, Jingsi Ming, Heng Peng, Jin Liu & Can Yang2020BIVAS: A Scalable Bayesian Method for Bi-Level Variable Selection With ApplicationsJournal of Computational and Graphical Statistics, 29:1, 40-52

  14. Dai, Linlin*, Chen, K. and Li, G. (2020). The broken adaptive ridge procedure and its applications. Statistica Sinica, 30, 1069-1094.

  15. Zhiyong Li, Xinyi Hu, Ke Li, Fanyin Zhou, Feng Shen Inferring the Outcomes of Rejected Loans: an Application of Semi-supervised ClusteringJournal of the Royal Statistical Society: Series A, (2020) 183, Part 2, 631654

  16. Yunbei Ma, Fanyin Zhou, and Xuan Luo (2020). Partial Derivatives Estimation for Underlying Functional-Valued Process in a Unified Framework. Journal of Applied Mathematics,2020:1-17

  17. Ma Dan, Liu Bin, Kang Zhao, Zhu Jianke, Xu Zenglin: 2020,Two Birds with One Stone: Iteratively Learn Facial Attributes with GANs.Neurocomputing. 396.278-290

  18. Lee, C. Y., Chen, X., & Lam, K. F. (2020). Testing for changepoint in the covariate effects based on the Cox regression model. Statistics in Medicine, 39(10), 1473-1488.

  19. Hong, H. G., Chen, X., Kang, J., & Li, Y. (2020). The Lq-norm learning for ultrahigh-dimensional survival data: an integrative framework. Statistica Sinica, 30(3), 121

  20. Hu, N., Chen, X., & Sun, J. (2020). Semiparametric Analysis of Short-Term and Long-Term Hazard Ratio Model with Length-Biased and Right-Censored Data. Statistica Sinica30, 487-509

  21. 张澍一,陈松蹊,郭斌,王恒放,林伟.(2020.气象调整下的区域空气质量评估[J].中国科学:数学,50(04):527-558.

  22. LaBarre, J. L., Puttabyatappa, M., Song, P. X., Goodrich, J. M., Zhou, L., Rajendiran, T. M., ... & Padmanabhan, V. (2020). Maternal lipid levels across pregnancy impact the umbilical cord blood lipidome and infant birth weight. Scientific reports, 10(1), 1-15.

  23. Tang, L., Zhou, L., & Song, P. X. K*. (2020). Distributed simultaneous inference in generalized linear models via confidence distribution. Journal of Multivariate Analysis, 176, 104567.

  24. Wu, L., & Chen, S. (2020). Long memory and efficiency of Bitcoin under heavy tails. Applied Economics, 52, NO. 48, 5298–5309.

  25. 吴量.(2020).有限二阶矩情形与重尾情形下的Hurst参数[J].数学物理学报,40(04):1072-1082.

  26. Wu, L. (2020). A Note on Wavelet-Based Estimator of the Hurst Parameter. Entropy, 22(3), 349.

  27. Wu, L., & Ding, Y. (2020). Wavelet-based estimations of fractional Brownian sheet: Least squares versus maximum likelihood. Journal of Computational and Applied Mathematics, 371, 112609.

  28. Lv, F., Liang, T., Chen, X., & Lin, G. (2020). Cross-Domain Semantic Segmentation via Domain-Invariant Interactive Relation Transfer. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 4334-4343).

  29. Feng, L., Shu, S., Lin, Z., Lv, F., Li, L., & An, B. (2020). Can Cross Entropy Loss Be Robust to Label Noise?. IJCAI. 2206-2212

  30. Yang, X., Lin, G., Lv, F., & Liu, F. (2020). TRRNet: Tiered Relation Reasoning for Compositional Visual Question Answering. ECCV,Doi: 10.1007/978-3-030-58589-1_25

  31. Lv, F., Liu, H., Wang, Y., Zhao, J., & Yang, G. (2020). Learning unbiased zero-shot semantic segmentation networks via transductive transfer. IEEE Signal Processing Letters, 27, 1640-1644.

  32. Cao, Z., Yang, G., Chen, Q., Chen, X., & Lv, F*. (2020). Breast tumor classification through learning from noisy labeled ultrasound images. Medical Physics, 47(3), 1048-1057.

  33. Liu, D., Yang, G., Li, Y., Wu, J., & Lv, F. (2020). Gradient boosting tree for H-MRS Alzheimer diagnosis. International Journal of Data Mining and Bioinformatics, 23(1), 12-29.

  34. Liyuan Zheng, Yajie Hu, Bin Liu*, (2020) Wei Deng, Learning robust word representation over a semantic manifold., Knowledge-Based Systems, Volume 192, 105358

 

上一条:2021年研究成果

下一条:2019年研究成果